U.S.-Korea Cooperative Research on Multiclass Queueing Networks

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9605190 Dai This award supports a three-year collaborative research project between Dr. Jian-Gang Dai, Georgia Institute of Technology, and Dr. Bok Sik Yoon, Hong-ik University, Seoul, Korea, on multiclass queuing networks. The focus of this research is the investigation of several aspects of multiclass queuing networks that arise from complex manufacturing systems. The scope of the research will range from the development of fundamental mathematical models of such networks to the computer implementation of the models for some real world applications. Specific research topics to be investigated include the scheduling of wafer fabrication lines, stability of multiclass queuing networks, Brownian models under non-first in first out (non-FIFO) policies, heavy traffic convergence, and computation of stationary distribution for a reflected Brownian motion (RBM). Brownian models have been proved to be effective for the approximate analysis of queuing networks. It has also been proved that FIFO which most Brownian models to date employ may be unstable in some networks. Brownian models also play important roles in both performance analysis and optimal or near optimal scheduling of queuing networks. The Brownian approximation will be used to analyze most queuing network models that are interesting in practice. The computer implementation of the Brownian approximation scheme will be used to predict the performances of a variety of queuing networks, including those that arise in manufacturing and telecommunication systems. This research effort will combine the expertise of the U. S. and Korean research scientists in a project of mutual interest and benefit. Korean participation is supported by the Korea Science and Engineering Foundation (KOSEF). This project adds an international cooperative dimension to research supported by NSF Grant No. DMI-9457336. ***